Journal Club

We will discuss about “Uncovering specific mechanisms across cell types in dynamical models”, Hauber, Adrian Lukas, Marcus Rosenblatt, and Jens Timmer., bioRxiv (2023): 2023-01. Abstract Ordinary differential equations are frequently employed for mathematical modeling of biological systems. The identification of mechanisms that are specific to certain cell types is crucial for building useful models and to …

We will discuss about “The energy cost and optimal design of networks for biological discrimination”, Yu, Qiwei, Anatoly B. Kolomeisky, and Oleg A. Igoshin., Journal of the Royal Society Interface 19.188 (2022): 20210883. Abstract Many biological processes discriminate between correct and incorrect substrates through the kinetic proofreading mechanism that enables lower error at the cost of …

We will discuss about “Wearable data science for personalized digital medicine” Abstract Millions of people currently use wearables such as the Apple Watch to monitor their physical activity, heart rate, and other physiological signals, generating an unprecedented amount of wearable data. This presents an opportunity for digital medicine to advance precision medicine. However, the noisy …

We will discuss about “scPrisma infers, filters and enhances topological signals in single-cell data using spectral template matching”, Karin, Jonathan, Yonathan Bornfeld, and Mor Nitzan., Nature Biotechnology (2023): 1-10. Abstract Single-cell RNA sequencing has been instrumental in uncovering cellular spatiotemporal context. This task is challenging as cells simultaneously encode multiple, potentially cross-interfering, biological signals. Here we …

We will discuss about “The singularity response reveals entrainment properties of the plant circadian clock”, Masuda, Kosaku, et al., Nature Communications 12.1 (2021): 864. Abstract Circadian clocks allow organisms to synchronize their physiological processes to diurnal variations. A phase response curve allows researchers to understand clock entrainment by revealing how signals adjust clock genes differently …

We will discuss about “ The Internal Model Principle for Biomolecular Control Theory ”, Gupta, Ankit, and Mustafa Khammash., IEEE Open Journal of Control Systems 2 (2023): 63-69.   Abstract The well-known Internal Model Principle (IMP) is a cornerstone of modern control theory. It stipulates the necessary conditions for asymptotic robustness of disturbance-prone dynamical systems …

We will discuss about “ Decomposing predictability to identify dominant causal drivers in complex ecosystems ”,Suzuki, Kenta, Shin-ichiro S. Matsuzaki, and Hiroshi Masuya., Proceedings of the National Academy of Sciences 119.42 (2022): e2204405119.   Abstract Ecosystems are complex systems of various physical, biological, and chemical processes. Since ecosystem dynamics are composed of a mixture of …

We will discuss about “Generalized Michaelis–Menten rate law with time-varying molecular concentrations”, Lim, Roktaek, et al.,bioRxiv (2022): 2022-01   Abstract The Michaelis–Menten (MM) rate law has been the dominant paradigm of modeling biochemical rate processes for over a century with applications in biochemistry, biophysics, cell biology, and chemical engineering. The MM rate law and its …

We will discuss about “Exact solution of a three-stage model of stochastic gene expression including cell-cycle dynamics”, Wang, Yiling, et al., bioRxiv (2023): 2023-08.   Abstract The classical three-stage model of stochastic gene expression predicts the statistics of single cell mRNA and protein number fluctuations as a function of the rates of promoter switching, transcription, translation, …

We will discuss about “Antithetic proportional-integral feedback for reduced variance and improved control performance of stochastic reaction networks ”,Briat, Corentin, Ankit Gupta, and Mustafa Khammash., Journal of The Royal Society Interface 15.143 (2018): 20180079 Abstract The ability of a cell to regulate and adapt its internal state in response to unpredictable environmental changes is called …

We will discuss about “A data-driven approach for timescale decomposition of biochemical reaction networks”, Amir Akbari, Zachary B. Haiman, Bernhard O. Palsson, bioRxiv (2023) Abstract Understanding the dynamics of biological systems in evolving environments is a challenge due to their scale and complexity. Here, we present a computational framework for timescale decomposition of biochemical reaction …

We will discuss about “Power spectral estimate for discrete data”, Nobert Marwan and Tobias Braun, Chaos (2023).   Abstract The identification of cycles in periodic signals is a ubiquitous problem in time series analysis. Many real-world datasets only record a signal as a series of discrete events or symbols. In some cases, only a sequence …